def test_can_identify_gradient_lr(self):
fg = self.create_fastgrid_from(
[64, 32, 16, 8, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32])
sut = ConvolutionKernel([[+0, +0, -0], [+1, +1, -1], [+0, +0, -0]])
new_array = sut.compute(fg)
self.assertIsNotNone(new_array)
def test_can_highlight_blocking_tiles_in_corner(self):
fg = self.create_fastgrid_from(
[2, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32])
# Sobel Operator: https://en.wikipedia.org/wiki/Sobel_operator
sut = ConvolutionKernel([[0, 0, 0], [0, +3, -1], [0, -1, -1]])
new_array = sut.compute(fg)
self.assertIsNotNone(new_array)
def test_can_highlight_checkerboard(self):
fg = self.create_fastgrid_from(
[2, 32, 32, 32, 8, 16, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32])
# Sobel Operator: https://en.wikipedia.org/wiki/Sobel_operator
sut = ConvolutionKernel([[-1, -1, -1], [-1, +8, -1], [-1, -1, -1]])
new_array = sut.compute(fg)
self.assertIsNotNone(new_array)
def test_can_detect_edge_2(self):
fg = self.create_fastgrid_from(
[0, 128, 0, 0, 0, 128, 0, 0, 0, 128, 0, 0, 0, 128, 0, 0])
# Sobel Operator: https://en.wikipedia.org/wiki/Sobel_operator
sut = ConvolutionKernel([[1, 0, -1], [2, 0, -2], [1, 0, -1]])
new_array = sut.compute(fg)
self.assertIsNotNone(new_array)
class ConvolutionKernelCalculator(UtilityCalculator):
def __init__(self):
self.hole_detector_kernel = ConvolutionKernel([[-1, -1, -1],
[-1, +8, -1],
[-1, -1, -1]])
def compute_utility(self, grid: FastGrid) -> float:
new_array = self.hole_detector_kernel.compute(grid)
result = sigmoid(sum(new_array))
return result
def __init__(self):
self.hole_detector_kernel = ConvolutionKernel([[-1, -1, -1],
[-1, +8, -1],
[-1, -1, -1]])
def test_can_highlight_stranded_high_tile(self):
fg = self.create_fastgrid_from(
[32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 128, 32, 32, 32, 32, 32])
sut = ConvolutionKernel([[-0, +1, +0], [+1, -5, +1], [-0, +1, +0]])
new_array = sut.compute(fg)
self.assertIsNotNone(new_array)
def test_can_highlight_high_tiles_in_corner(self):
fg = self.create_fastgrid_from(
[1024, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32, 32])
sut = ConvolutionKernel([[0, 0, 0], [0, +3, -1], [0, -1, -1]])
new_array = sut.compute(fg)
self.assertIsNotNone(new_array)
def test_incorrect_dimensions_should_cause_exception(self):
incorrect = [[1, 2], [1, 2]]
with self.assertRaises(ValueError) as context:
sut = ConvolutionKernel(incorrect)
def test_can_compute_doubling_kernel(self):
fg = self.create_random_fastgrid()
sut = ConvolutionKernel([[0, 0, 0], [0, 2, 0], [0, 0, 0]])
for y in range(4):
for x in range(4):
self.assertEqual(2 * fg[x, y], sut.compute_point(x, y, fg))
def test_can_create_kernel(self):
correct = [[1, 2, 3], [1, 2, 3], [1, 2, 3]]
sut = ConvolutionKernel(correct)
self.assertIsNotNone(sut)